Memetic computing is a subject in computer science which considers complex structures
such as the combination of simple agents and memes, whose evolutionary interactions lead …

In recent years, there has been a growing interest for the experimental analysis in the field of
evolutionary algorithms. It is noticeable due to the existence of numerous papers which …

Memetic computation is a paradigm that uses the notion of meme (s) as units of information
encoded in computational representations for the purpose of problem-solving. It covers a …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

In the last years, there has been a growing interest for the experimental analysis in the field
of evolutionary algorithms. It is noticeable due to the existence of numerous papers which …

Many different algorithms have been developed in the last few decades for solving complex
real-world search and optimization problems. The main focus in this research has been on …

Structured population in evolutionary algorithms is a vital strategy to control diversity during
the search. One of the most popular structured population strategies is the island model in …

Hill climbing method is an optimization technique that is able to build a search trajectory in
the search space until reaching the local optima. It only accepts the uphill movement which …

Memetic algorithms (MAs) represent one of the recent growing areas in evolutionary
algorithm (EA) research. The term MAs is now widely used as a synergy of evolutionary or …

Memetic algorithms with continuous local search methods have arisen as effective tools to
address the difficulty of obtaining reliable solutions of high precision for complex continuous …